EAGER: Fabrication of Thin, Lens-Free Cameras for Visible and SWIR Imaging
EAGER:制造用于可见光和短波红外成像的薄型无镜头相机
基本信息
- 批准号:1502875
- 负责人:
- 金额:$ 15万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2015
- 资助国家:美国
- 起止时间:2015-02-01 至 2017-01-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Image sensors have benefited immensely from the steady advances in semiconductor fabrication, resulting in an order of magnitude resolution increase every decade for the last three decades. Moore?s law has had a similar impact on both computing and image sensor technology. In addition to the sensor, however, cameras and other imaging devices require lenses whose manufacturing processes has not benefited from Moore?s law. As a result the ultimate scaling and cost of imaging devices is limited by physical optics. This research project involves the development of Lens-Free Cameras (LFCs), a novel imaging architecture for visible, short-wave infrared (SWIR), mid-wave infrared (MWIR) and thermal wavelengths that exploits amplitude multiplexing masks and computational demultiplexing algorithms to replace lenses in traditional cameras. Such lensless imaging technology will produce thin cameras that can be directly fabricated using contemporary semiconductor fabrication processes, thereby benefitting from the scaling laws of semiconductor fabrication.An LFC consists of an image sensor and a thin amplitude modulation mask fabricated at a few hundreds of microns above the image sensor surface. The amplitude modulation mask creates a linear mapping between the scene and the sensor measurements. The linear system describing the LFC contains millions of variables and millions of measurements. Solving this large linear system of equations will allow for the reconstruction of high resolution images from the sensor measurements. This project will focus on the fabrication of a thin lensfree camera. The result of this fabrication process will be the world?s first camera less than a millimeter thick. The advance in lensfree cameras will be more widely applicable to several challenging applications such as microscopy, endoscopy and other space constrained imaging scenarios.
图像传感器从半导体制造的稳步发展中受益匪浅,在过去的三十年中,每十年就有一个数量级的分辨率增加。摩尔?S定律对计算和图像传感器技术都产生了类似的影响。然而,除了传感器之外,相机和其他成像设备也需要镜头,而这些镜头的制造工艺并没有从摩尔?年代法律。因此,成像器件的最终规模和成本受到物理光学的限制。该研究项目涉及无镜头相机(lfc)的开发,这是一种用于可见光、短波红外(SWIR)、中波红外(MWIR)和热波长的新型成像架构,利用幅度复用掩模和计算解复用算法来取代传统相机中的镜头。这种无透镜成像技术将生产薄相机,可以直接使用现代半导体制造工艺制造,从而受益于半导体制造的缩放定律。LFC由图像传感器和在图像传感器表面上方几百微米处制作的薄调幅掩模组成。调幅掩模在场景和传感器测量之间创建线性映射。描述LFC的线性系统包含数百万个变量和数百万个测量值。求解这个大型线性方程组将允许从传感器测量中重建高分辨率图像。这个项目将专注于制造一个薄的无镜头相机。这个制造过程的结果将是世界?这是美国首款厚度不到一毫米的相机。无镜头相机的进步将更广泛地适用于一些具有挑战性的应用,如显微镜、内窥镜检查和其他空间受限的成像场景。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Ashok Veeraraghavan其他文献
PPGMotion: Model-based detection of motion artifacts in photoplethysmography signals
PPGMotion:基于模型的光电容积描记术信号中运动伪影的检测
- DOI:
10.1016/j.bspc.2022.103632 - 发表时间:
2022-05-01 - 期刊:
- 影响因子:4.900
- 作者:
Akash Kumar Maity;Ashok Veeraraghavan;Ashutosh Sabharwal - 通讯作者:
Ashutosh Sabharwal
Generalization Error
泛化错误
- DOI:
- 发表时间:
2009 - 期刊:
- 影响因子:0
- 作者:
Ramalingam Chellappa;Ashok Veeraraghavan;Narayanan Ramanathan;Chew;M. S. Nixon;A. Elgammal;Jeffrey E. Boyd;J. Little;Niels Lynnerup;Peter K. Larsen;Douglas A. Reynolds - 通讯作者:
Douglas A. Reynolds
Neural Wavefront Shaping in the Photon-Starved Regime
光子匮乏状态下的神经波前整形
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Brandon Y. Feng;Haiyun Guo;Mingyang Xie;Vivek Boominathan;Manoj K. Sharma;Ashok Veeraraghavan;Christopher A. Metzler - 通讯作者:
Christopher A. Metzler
Unsupervised view and rate invariant clustering of video sequences q
视频序列 q 的无监督视图和速率不变聚类
- DOI:
- 发表时间:
2009 - 期刊:
- 影响因子:0
- 作者:
P. Turaga;Ashok Veeraraghavan;Rama Chellappa - 通讯作者:
Rama Chellappa
Ieee Transactions on Pattern Analysis and Machine Intelligence Shape and Behavior Encoded Tracking of Bee Dances Ieee Transactions on Pattern Analysis and Machine Intelligence 2
IEEE 模式分析和机器智能交易 蜜蜂舞蹈的形状和行为编码跟踪 IEEE 模式分析和机器智能交易 2
- DOI:
- 发表时间:
- 期刊:
- 影响因子:0
- 作者:
Ashok Veeraraghavan;Ramalingam Chellappa - 通讯作者:
Ramalingam Chellappa
Ashok Veeraraghavan的其他文献
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{{ truncateString('Ashok Veeraraghavan', 18)}}的其他基金
Collaborative Research: RI: Medium: Thermal Computational Imaging
合作研究:RI:媒介:热计算成像
- 批准号:
2107313 - 财政年份:2021
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
Collaborative Research: CNS Core: Medium: OneDegree: Foundations and Methods for Imaging in mmWave Wireless Networks
合作研究:CNS 核心:Medium:OneDegree:毫米波无线网络成像的基础和方法
- 批准号:
1956297 - 财政年份:2020
- 资助金额:
$ 15万 - 项目类别:
Continuing Grant
SaTC: CORE: Medium: Collaborative: Presentation-attack-robust biometrics systems via computational imaging of physiology and materials
SaTC:核心:中:协作:通过生理学和材料的计算成像实现演示攻击鲁棒生物识别系统
- 批准号:
1801372 - 财政年份:2018
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
CAREER: A Signal Processing Framework for Computational Imaging: From Theory to Applications
职业:计算成像信号处理框架:从理论到应用
- 批准号:
1652633 - 财政年份:2017
- 资助金额:
$ 15万 - 项目类别:
Continuing Grant
I-Corps: TEAMS-MobileVision from Advanced Vision Labs
I-Corps:来自高级视觉实验室的 TEAMS-MobileVision
- 批准号:
1505693 - 财政年份:2014
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
CIF: Small: Computational Tools for Visual Inference of Complex Materials
CIF:小型:复杂材料视觉推理的计算工具
- 批准号:
1117939 - 财政年份:2011
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
CGV: Small: Collaborative Research: AdaCID: Adaptive Coded Imaging and Displays
CGV:小型:协作研究:AdaCID:自适应编码成像和显示
- 批准号:
1116718 - 财政年份:2011
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
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